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Article
Publication date: 24 September 2019

Yezhong Fang, Xiaotian Ji, Xingquan Zhang, Jun Wang, Bin Chen, Shiwei Duan, Jinyu Tong, Guangwu Fang and Shanbao Pei

The purpose of this paper is to investigate the dynamic forming process of the micro dent fabricated by laser shock processing on 2024-T3 aluminum alloy. The effect of laser pluse…

177

Abstract

Purpose

The purpose of this paper is to investigate the dynamic forming process of the micro dent fabricated by laser shock processing on 2024-T3 aluminum alloy. The effect of laser pluse energy on the deformation of micro dent was also discussed in detail.

Design/methodology/approach

It uses finite element analysis method and the corresponding laser shocking experiment.

Findings

The results demonstrate that the dynamic formation process of micro dent lasts longer in comparison with the shock wave loading time, and the depths of micro dents increase with the increasing laser energy. In addition, laser shocking with higher energy can result in more obvious pileup occurred at the outer edge of micro dent.

Originality/value

Surface micro dents can serve as fluid reservoirs and traps of the wear debris, which can decrease the effects of the wear and friction in rolling and sliding interfaces. The investigations can not only be propitious to comprehensively understand the forming mechanism of laser-shocked dent, but also be beneficial to get sight into the residual stress field induced by laser shocking.

Details

Multidiscipline Modeling in Materials and Structures, vol. 16 no. 1
Type: Research Article
ISSN: 1573-6105

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Article
Publication date: 27 May 2024

Min Li, Hangxuan Liu, Xingquan Zhang, Hengji Yang, Lisheng Zuo, Ziyu Wang, Shiwei Duan and Song Shu

The purpose of this paper is to investigate the effect of laser peening (LP) on mechanical and wear properties of 304 stainless steel sheet.

134

Abstract

Purpose

The purpose of this paper is to investigate the effect of laser peening (LP) on mechanical and wear properties of 304 stainless steel sheet.

Design/methodology/approach

Three-dimensional morphology, micro-hardness and micro-structure of shocked samples were tested. The wear amount, wear track morphology and wear mechanism were also characterized under dry sliding wear using Al2O3 ceramics ball.

Findings

The LP treatment generates deformation twins that contribute to the grain refinement and hardness increase. The wear test displays that the wear mechanism of samples is mainly abrasive wear and oxidation wear at 10 N load. While at 30 N, the delamination and adhesion areas of treated sample are reduced visibly compared to untreated ones.

Originality/value

This study specifically investigates the mechanical and wear properties of 304 stainless steel after the direct action of LP on its surface, which shows an effective improvement on the wear resistance. For example, the wear loss of processed sample is reduced by 19% at 30 N, the friction coefficient decreases from 0.4714 to 0.4308 and the groove depth is reduced from 78.1 to 74.4 µm under same condition.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0007/

Details

Industrial Lubrication and Tribology, vol. 76 no. 5
Type: Research Article
ISSN: 0036-8792

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Article
Publication date: 18 March 2022

Pinsheng Duan, Jianliang Zhou and Shiwei Tao

The outbreak of the pandemic makes it more difficult to manage the safety or health of construction workers in infrastructure construction. Risk events in construction workers'…

454

Abstract

Purpose

The outbreak of the pandemic makes it more difficult to manage the safety or health of construction workers in infrastructure construction. Risk events in construction workers' material handling tasks are highly relevant to workers' work-related musculoskeletal disorders. However, there are still many problems to be resolved in recognizing risk events accurately. The purpose of this research is to propose an automatic and non-invasive recognition method for construction workers in material handling tasks during the pandemic based on smartphone and machine learning.

Design/methodology/approach

This research proposes a method to recognize and classify four different risk events by collecting specific acceleration and angular velocity patterns through built-in sensors of smartphones. The events were simulated with anterior handling and shoulder handling methods in the laboratory. After data segmentation and feature extraction, five different machine learning methods are used to recognize risk events and the classification performances are compared.

Findings

The classification result of the shoulder handling method was slightly better than the anterior handling method. By comparing the accuracy of five different classifiers, cross-validation results showed that the classification accuracy of the random forest algorithm was the highest (76.71% in anterior handling method and 80.13% in shoulder handling method) when the window size was 0.64 s.

Originality/value

Less attention has been paid to the risk events in workers' material handling tasks in previous studies, and most events are recorded by manual observation methods. This study provided a simple and objective way to judge the risk events in manual material handling tasks of construction workers based on smartphones, which can be used as a non-invasive way for managers to improve health and labor productivity during the pandemic.

Details

Engineering, Construction and Architectural Management, vol. 30 no. 8
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 14 February 2025

Xuemei Li, Yuyu Sun, Yansong Shi, Yufeng Zhao and Shiwei Zhou

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote…

6

Abstract

Purpose

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote sustainable transportation development.

Design/methodology/approach

This paper introduces a novel self-adaptive grey multivariate prediction modeling framework (FARDCGM(1,N)) to forecast port cargo throughput in China, addressing the challenges posed by mutations and time lag characteristics of time series data. The model explores policy-driven mechanisms and autoregressive time lag terms, incorporating policy dummy variables to capture deviations in system development trends. The inclusion of autoregressive time lag terms enhances the model’s ability to describe the evolving system complexity. Additionally, the fractional-order accumulative generation operation effectively captures data features, while the Grey Wolf Optimization algorithm determines optimal nonlinear parameters, enhancing the model’s robustness.

Findings

Verification using port cargo throughput forecasts for FTZs in Shanghai, Guangdong and Zhejiang provinces demonstrates the FARDCGM(1,N) model’s remarkable accuracy and stability. This innovative model proves to be an excellent forecasting tool for systematically analyzing port cargo throughput under external interventions and time lag effects.

Originality/value

A novel self-adaptive grey multivariate modeling framework, FARDCGM(1,N), is introduced for accurately predicting port cargo throughput, considering policy-driven impacts and autoregressive time-lag effects. The model incorporates the GWO algorithm for optimal parameter selection, enhancing adaptability to sudden changes. It explores the dual role of policy variables in influencing system trends and the impact of time lag on dynamic response rates, improving the model’s complexity handling.

Details

Grey Systems: Theory and Application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 13 December 2024

Weilang Cai, Dongqi Hua, Sihao Li, Shiwei Xue and Zhao Xu

BIM technology has a huge potential for improving the renovation efficiency for as-built buildings. However, due to the absence of raw design drawings and the complex interior…

52

Abstract

Purpose

BIM technology has a huge potential for improving the renovation efficiency for as-built buildings. However, due to the absence of raw design drawings and the complex interior environment, it is difficult to implement 3D reconstruction of building interiors in interior renovation projects. Therefore, this study proposes a 3D reconstruction framework of building interiors, with an aim to generate building interiors building information modeling (BIM) models quickly and accurately based on scan-to-BIM and generative design.

Design/methodology/approach

The proposed framework begins by reconstructing interior structured elements based on the scan-to-BIM process including collecting accurate information of as-built buildings by laser scanning, obtaining point clouds of structured elements through deep learning and developing an efficient dynamo algorithm workflow for generating structured elements BIM model. For unstructured elements, intelligent layout design and efficient BIM generation are conducted by combining the BIM tools and generative design.

Findings

The successful implementation of the proposed framework in a conference room demonstrated the feasibility of the proposed framework. The semantic segmentation scheme based on deep learning also exhibited excellent recognition and high efficiency for interior structured elements. Furthermore, it is proved that the combination of scan-to-BIM and generative design has high application value in the 3D reconstruction of building interiors.

Originality/value

On one hand, a feasible framework is proposed to generate BIM model of building interiors, improve interoperability among different software tools, streamline the complexity of the scan-to-BIM process and meet the reconfiguration requirement of unstructured elements layout scheme in interior renovation projects. On the other hand, the use of BIM and various emerging technologies can drive digital transformation and further advance the industrialization process of interior renovation in as-built buildings.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Available. Open Access. Open Access
Article
Publication date: 22 November 2022

Kedong Yin, Yun Cao, Shiwei Zhou and Xinman Lv

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems…

998

Abstract

Purpose

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Design/methodology/approach

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Findings

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

Originality/value

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Details

Marine Economics and Management, vol. 5 no. 2
Type: Research Article
ISSN: 2516-158X

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Article
Publication date: 11 September 2024

Zijian Wang, Ximing Xiao, Shiwei Fu and Qinggong Shi

This study aims to uncover the mechanisms behind the marginalization of county-level public libraries.

47

Abstract

Purpose

This study aims to uncover the mechanisms behind the marginalization of county-level public libraries.

Design/methodology/approach

The research surveyed 25 counties in central China, including Hubei, Chongqing, Hunan, and Guizhou provinces. Semi-structured interviews were conducted with library directors and deputy directors, focusing on main and branch library construction, cultural inclusivity, library assessment, and digital services.

Findings

Contributing factors to library marginalization were identified as economic pressure, institutional domain, longstanding issues, organizational entity, and societal misconceptions. Building on this, the study introduces the HBAC model to explain county-level public library marginalization. Considering the actual social context of these libraries, the article proposes a “3 + 1” approach to mitigate their marginalization.

Originality/value

The research methodology, analysis process, theoretical model, and recommendations provided could shed light on academic research and practical exploration in the field of public libraries globally.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

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